Triple
T6623798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volodymyr Groysman |
E149743
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Groysman
Groysman is a Ukrainian surname most prominently associated with Volodymyr Groysman, a former Prime Minister of Ukraine.
|
E601231
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Groysman | Statement: [Volodymyr Groysman, familyName, Groysman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Groysman Context triple: [Volodymyr Groysman, familyName, Groysman]
-
A.
Halsema
Halsema is a Dutch surname most prominently associated with Femke Halsema, a politician who became the first female mayor of Amsterdam.
-
B.
Ervin
Ervin is a masculine given name of Germanic origin, closely related to names like Erwin and Irvin.
-
C.
Don Roos
Don Roos is an American screenwriter and film director known for his sharp, darkly comedic dramas such as "The Opposite of Sex" and "Happy Endings."
-
D.
Walter Orange
Walter Orange is an American singer, drummer, and songwriter best known as a key member and lead vocalist of the funk and soul band the Commodores.
-
E.
Olitski
Olitski is the surname of Jules Olitski, a prominent Russian-American abstract painter associated with Color Field painting and the Washington Color School.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Groysman Triple: [Volodymyr Groysman, familyName, Groysman]
Generated description
Groysman is a Ukrainian surname most prominently associated with Volodymyr Groysman, a former Prime Minister of Ukraine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Groysman Target entity description: Groysman is a Ukrainian surname most prominently associated with Volodymyr Groysman, a former Prime Minister of Ukraine.
-
A.
Halsema
Halsema is a Dutch surname most prominently associated with Femke Halsema, a politician who became the first female mayor of Amsterdam.
-
B.
Ervin
Ervin is a masculine given name of Germanic origin, closely related to names like Erwin and Irvin.
-
C.
Don Roos
Don Roos is an American screenwriter and film director known for his sharp, darkly comedic dramas such as "The Opposite of Sex" and "Happy Endings."
-
D.
Walter Orange
Walter Orange is an American singer, drummer, and songwriter best known as a key member and lead vocalist of the funk and soul band the Commodores.
-
E.
Olitski
Olitski is the surname of Jules Olitski, a prominent Russian-American abstract painter associated with Color Field painting and the Washington Color School.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af7fc054819099a2e58cefd8fed7 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbe2bcfc8190a3224c688443edc9 |
completed | March 27, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69c6cd89b51c81909ea17d391732630e |
completed | March 27, 2026, 6:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6ce70442c8190a12a6c6eb76c5269 |
completed | March 27, 2026, 6:37 p.m. |
Created at: March 27, 2026, 1:58 p.m.